百度了一圈没有靠谱点的答案,于是便有了这篇博客。 只写了一些自己觉得有价值的习题。
证明: 当 n = 6 m + 5 n=6m+5 n=6m+5时,多项式 x 2 + x y + y 2 x^2+xy+y^2 x2+xy+y2整除多项式 ( x + y ) n − x n − y n (x+y)^n-x^n-y^n (x+y)n−xn−yn; 当 n = 6 m + 1 n=6m+1 n=6m+1时,多项式 ( x 2 + x y + y 2 ) 2 (x^2+xy+y^2)^2 (x2+xy+y2)2整除多项式 ( x + y ) n − x n − y n (x+y)^n-x^n-y^n (x+y)n−xn−yn.这里 m m m是使 n > 0 n>0 n>0的整数,而 x , y x,y x,y是实数.
注意到 x 2 + x + 1 x^2+x+1 x2+x+1的根 w w w为三次单位根,且 w + 1 w+1 w+1为6次单位根.
用归纳法,对于 6 m + 5 6m+5 6m+5的情况,只需计算 f ( w ) f(w) f(w)是否为0,对于 6 m + 1 6m+1 6m+1的情况还需计算 f ′ ( w ) f'(w) f′(w).
设 f ( x ) f(x) f(x)是 2 n + 1 2n+1 2n+1次多项式, n n n为正整数, f ( x ) + 1 f(x)+1 f(x)+1被 ( x − 1 ) n (x-1)^n (x−1)n整除, f ( x ) − 1 f(x)-1 f(x)−1被 ( x + 1 ) n (x+1)^n (x+1)n整除.求 f ( x ) f(x) f(x).
First we have: u ( x ) ( x − 1 ) n − 1 = v ( x ) ( x + 1 ) n + 1 u(x)(x-1)^n - 1 = v(x)(x+1)^n + 1 u(x)(x−1)n−1=v(x)(x+1)n+1
Because of ( ( x − 1 ) n , ( x + 1 ) n ) = 1 ((x-1)^n,(x+1)^n)=1 ((x−1)n,(x+1)n)=1,there exists u ( x ) , v ( x ) u(x),v(x) u(x),v(x), such that:
u ( x ) ( x − 1 ) n − v ( x ) ( x + 1 ) n = 2 u(x)(x-1)^n - v(x)(x+1)^n = 2 u(x)(x−1)n−v(x)(x+1)n=2
if we find such u ( x ) , v ( x ) u(x),v(x) u(x),v(x),then ( u ( x ) + t ( x ) ∗ ( x + 1 ) n ) ( x − 1 ) n − 1 (u(x)+t(x)*(x+1)^n)(x-1)^n - 1 (u(x)+t(x)∗(x+1)n)(x−1)n−1 could be a valid f ( x ) f(x) f(x).
Notice that there exists a u ( x ) u(x) u(x), d e g ( u ( x ) ) < n deg(u(x)) < n deg(u(x))<n,then because: u ( x ) = ( 1 − v ( x ) ( x + 1 ) n ) ( x − 1 ) − n u(x) = (1-v(x)(x+1)^n)(x-1)^{-n} u(x)=(1−v(x)(x+1)n)(x−1)−n So: u ( i ) ( − 1 ) = ( ∏ j = 0 i − 1 ( − n − j ) ) ( − 2 ) − n − i u^{(i)}(-1) = (\prod_{j=0}^{i-1}(-n-j)) (-2)^{-n-i} u(i)(−1)=(j=0∏i−1(−n−j))(−2)−n−i
Use Taylor’s expansion: u ( x ) = ∑ i = 0 n − 1 u ( i ) ( − 1 ) i ! ( x + 1 ) i u(x) = \sum_{i=0}^{n-1}\frac{u^{(i)}(-1)}{i!}(x+1)^i u(x)=i=0∑n−1i!u(i)(−1)(x+1)i
尝试构造 n n n次单位根.
一个小Trick: x 4 − a x 2 + 1 = ( x 2 + 1 ) 2 − ( 2 + a ) x 2 = ( x 2 + 2 + a x + 1 ) ( x 2 − 2 + a x + 1 ) x^4-ax^2+1=(x^2+1)^2-(2+a)x^2 = (x^2+\sqrt{2+a}x+1)(x^2-\sqrt{2+a}x + 1) x4−ax2+1=(x2+1)2−(2+a)x2=(x2+2+a x+1)(x2−2+a x+1)
证明:实系数多项式 f ( x ) f(x) f(x)对所有实数 x x x恒取非负实数值的充分必要条件是,存在实系数多项式 φ ( x ) , ψ ( x ) \varphi(x),\psi(x) φ(x),ψ(x),使得 f ( x ) = [ φ ( x ) ] 2 + [ ψ ( x ) ] 2 f(x) = [\varphi(x)]^2 + [\psi(x)]^2 f(x)=[φ(x)]2+[ψ(x)]2.
f ( x ) = g ( x ) [ ( x − z 1 ) . . . ( x − z t ) ] [ ( x − z 1 ˉ ) . . . ( x − z t ˉ ) ] = g ( x ) ( p ( x ) + i q ( x ) ) ( p ( x ) − i q ( x ) ) = ( g ( x ) p ( x ) ) 2 + ( g ( x ) q ( x ) ) 2 \begin{aligned}f(x)&=g(x)[(x-z_1)...(x-z_t)][(x-\bar{z_1})...(x-\bar{z_t})]\\&=g(x)(p(x)+iq(x))(p(x)-iq(x)) \\&= (\sqrt{g(x)}p(x))^2 + (\sqrt{g(x)}q(x))^2\end{aligned} f(x)=g(x)[(x−z1)...(x−zt)][(x−z1ˉ)...(x−ztˉ)]=g(x)(p(x)+iq(x))(p(x)−iq(x))=(g(x) p(x))2+(g(x) q(x))2
证明分圆多项式在 Z \Z Z上不可约
f ( x ) = x p − 1 x − 1 f(x) = \frac{x^p-1}{x-1} f(x)=x−1xp−1,根为 w 1 , . . . , w p − 1 w^1,...,w^{p-1} w1,...,wp−1, p p p为奇数,又 ( x − w i ) ( x − w p − 1 ) (x-w^i)(x-w^{p-1}) (x−wi)(x−wp−1)不是有理系数,故不可约.
设 a 1 , . . . , a n a_1,...,a_n a1,...,an是 n n n个不同的整数, n ≥ 2 n \ge 2 n≥2,证明:多项式 ∏ i ( x − a i ) − 1 \prod_i (x-a_i) -1 ∏i(x−ai)−1在 Q \mathbb{Q} Q上不可约.
反证.设 f ( x ) = g ( x ) h ( x ) f(x)=g(x)h(x) f(x)=g(x)h(x),则 g ( x ) , h ( x ) g(x),h(x) g(x),h(x)在 n n n个点上取相反数,故 g ( x ) + h ( x ) = 0 ⇒ g ( x ) = − h ( x ) ⇒ f ( x ) = − g 2 ( x ) g(x)+h(x)=0 \Rightarrow g(x)=-h(x) \Rightarrow f(x)=-g^2(x) g(x)+h(x)=0⇒g(x)=−h(x)⇒f(x)=−g2(x)与 f ( x ) f(x) f(x)首项为1矛盾.
设 f ( x ) = ∑ i = 0 n a i x i f(x)=\sum_{i=0}^na_ix^i f(x)=∑i=0naixi是整系数多项式,且素数 p p p满足: p ∤ a 0 , p ∤ a 1 , . . . , p ∤ a k , p ∣ a k + 1 , . . . , p ∣ a n , p 2 ∤ a n p\not |a_0, p \not | a_1, ..., p \not | a_k, p|a_{k+1},...,p|a_n, p^2 \not| a_n p∣a0,p∣a1,...,p∣ak,p∣ak+1,...,p∣an,p2∣an.证明 f ( x ) f(x) f(x)具有次数 ≥ n − k \ge n-k ≥n−k的整系数不可约因式.
反证.设$f(x)=g(x)h(x)$,$g(x)=\sum_{i=0}^sb_ix^i$,$h(x)=\sum_{i=0}^tc_ix^i$,$p|b_s,p\not|c_t,p\not|b_0,p\not |c_1$,则$\exist m, p \not | b_{s-m}, p|b_{s-m+1},p|_{s-m+2}... \Rightarrow p \not|a_{n-m} \Rightarrow n-m \le k \Rightarrow m \ge n-k$,对$g$进行归纳.设整系数多项式 f ( x ) f(x) f(x)在 x x x的 4 4 4个不同整数值上取值为 1 1 1,则 f ( x ) f(x) f(x)在 x x x的其他整数值上的值不能是 − 1 -1 −1.
证明是显然的.
证明:设正整数 n ≥ 12 n \ge 12 n≥12,并且 n n n次整系数多项式 f ( x ) f(x) f(x)在 x x x的 ⌊ n 2 ⌋ + 1 \lfloor\frac{n}{2}\rfloor + 1 ⌊2n⌋+1个以上的整数值上取值为 ± 1 \pm 1 ±1,则 f ( x ) f(x) f(x)在 Q \mathbb{Q} Q上不可约.
根据习题6,取值必然全为 1 1 1或全为 − 1 -1 −1,然后反证, f = g h f=gh f=gh,则 g = − h g=-h g=−h或 g = h g=h g=h, f = − g 2 f=-g^2 f=−g2或 f = g 2 f=g^2 f=g2,分别与取值为正和取值为负矛盾.
设整系数多项式 a x 2 + b x + 1 ax^2+bx+1 ax2+bx+1在有理数域 Q \mathbb{Q} Q上不可约,并且 φ ( x ) = ∏ i ( x − a i ) \varphi(x)=\prod_{i}(x-a_i) φ(x)=∏i(x−ai),其中 a 1 , a 2 , . . . , a n a_1,a_2,...,a_n a1,a2,...,an是 n n n个不同的整数, n ≥ 7 n \ge 7 n≥7,证明:多项式 f ( x ) = a [ φ ( x ) ] 2 + b φ ( x ) + 1 f(x) = a[\varphi(x)]^2+b\varphi(x)+1 f(x)=a[φ(x)]2+bφ(x)+1在 Q \mathbb{Q} Q上不可约.
反证. f ( x ) = g ( x ) h ( x ) f(x)=g(x)h(x) f(x)=g(x)h(x)在 n n n个点上取1,则 g = h ⇒ f = g 2 ⇒ g g=h \Rightarrow f=g^2 \Rightarrow g g=h⇒f=g2⇒g在 n n n个点取1 ⇒ g = c φ ( x ) + 1 ⇒ f ( x ) = ( c φ ( x ) + 1 ) 2 \Rightarrow g = c\varphi(x)+1 \Rightarrow f(x)=(c\varphi(x)+1)^2 ⇒g=cφ(x)+1⇒f(x)=(cφ(x)+1)2与 a x 2 + b x + 1 ax^2+bx+1 ax2+bx+1不可约矛盾.
设三次方程 x 3 + a x 2 + b x + c x^3+ax^2+bx+c x3+ax2+bx+c的三个根是某个三角形的内角的正弦.证明: a ( 4 a b − a 3 − 8 c ) = 4 c 2 a(4ab-a^3-8c)=4c^2 a(4ab−a3−8c)=4c2
证明:利用海伦公式化简即可.
设对称多项式 f ( x 1 , x 2 , . . . , x n ) f(x_1,x_2,...,x_n) f(x1,x2,...,xn)满足: f ( x 1 + a , x 2 + a , . . . , x n + a ) = f ( x 1 , x 2 , . . . , x n ) f(x_1+a,x_2+a,...,x_n+a) = f(x_1,x_2,...,x_n) f(x1+a,x2+a,...,xn+a)=f(x1,x2,...,xn), a a a 为任意常数.设 f ( x 1 , x 2 , . . . , x n ) = g ( σ 1 , σ 2 , . . . , σ n ) f(x_1,x_2,...,x_n) = g(\sigma_1,\sigma_2,...,\sigma_n) f(x1,x2,...,xn)=g(σ1,σ2,...,σn).证明: ∑ i = 1 n ( n − i + 1 ) σ i − 1 ∂ g ∂ σ i = 0 \sum_{i=1}^{n}(n-i+1)\sigma_{i-1}\frac{\partial g}{\partial \sigma_{i}} = 0 ∑i=1n(n−i+1)σi−1∂σi∂g=0
证:首先 ∑ i ∂ σ k x i = ( n − k + 1 ) σ k − 1 \sum_i\frac{\partial \sigma_k}{x_i} = (n-k+1)\sigma_{k-1} ∑ixi∂σk=(n−k+1)σk−1,由题 ∑ i = 1 n ∂ f ∂ x i = 0 \sum_{i=1}^n \frac{\partial f}{\partial x_i} = 0 ∑i=1n∂xi∂f=0
∑ i = 1 n ∂ f ∂ x i = ∑ i = 1 n ∂ g ∂ σ i ∑ j ∂ σ i x j = ∑ i = 1 n ( n − i + 1 ) σ i − 1 ∂ g ∂ σ i = 0 \begin{aligned} \sum_{i=1}^n \frac{\partial f}{\partial x_i} &= \sum_{i=1}^n \frac{\partial g}{\partial \sigma_i}\sum_{j}\frac{\partial \sigma_i}{x_j} \\&= \sum_{i=1}^n(n-i+1)\sigma_{i-1} \frac{\partial g}{\partial \sigma_i} = 0\end{aligned} i=1∑n∂xi∂f=i=1∑n∂σi∂gj∑xj∂σi=i=1∑n(n−i+1)σi−1∂σi∂g=0
由牛顿多项式确定方程组后套用Cramer法则.
对10可利用归纳:
若多项式 f ( x 1 , x 2 , x 3 , . . . , x n ) = f ( x 2 , x 3 , . . . , x n , x 1 ) = f ( x 3 , . . . , x n , x 1 , x 2 ) = . . . f(x_1,x_2,x_3,...,x_n) = f(x_2,x_3,...,x_n,x_1) = f(x_3,...,x_n,x_1,x_2)=... f(x1,x2,x3,...,xn)=f(x2,x3,...,xn,x1)=f(x3,...,xn,x1,x2)=...则称 f ( x 1 , . . . , x n ) f(x_1,...,x_n) f(x1,...,xn)在未定元 f ( x 1 , . . . , x n ) f(x_1,...,x_n) f(x1,...,xn)的循环变换下不变, 证明: f f f在这种条件下可由 g 0 , . . . , g 1 g_0,...,g_1 g0,...,g1表示,其中 g j ( x 1 , . . . , x n ) = ∑ i = 1 n x i w i j g_j(x_1,...,x_n) = \sum_{i=1}^{n}x_i w^{ij} gj(x1,...,xn)=∑i=1nxiwij, w w w为 n n n次单位根,进一步的, f f f可表示为:
∑ m 0 , m 1 , . . . , m n − 1 a m 0 , m 1 , . . . , m n − 1 g 0 m 0 . . . g n − 1 m n − 1 \sum_{m_0,m_1,...,m_{n-1}}a_{m_0,m_1,...,m_{n-1}}g_0^{m_0}...g_{n-1}^{m_{n-1}} ∑m0,m1,...,mn−1am0,m1,...,mn−1g0m0...gn−1mn−1
其中 m 1 + 2 m 2 + . . . + ( n − 1 ) m n − 1 m_1+2m_2+...+(n-1)m_{n-1} m1+2m2+...+(n−1)mn−1能被 n n n整除,且 ∑ i m i ≤ deg ( f ) \sum_im_i \le \deg(f) ∑imi≤deg(f).
证明:
首先:
{ g 0 = x 0 + x 1 + x 2 + . . . + x n g 1 = x 0 + x 1 w + x 2 w 2 + . . . + x n w n ⋯ g n − 1 = x 0 + x 1 w n − 1 + x 2 w 2 ( n − 1 ) + . . . + x n w n ( n − 1 ) \begin{cases}g_0 &=& x_0 &+& x_1 &+& x_2&+& ... &+& x_n\\g_1 &=& x_0 &+& x_1w&+&x_2w^2 &+& ... &+& x_nw^n \\ \cdots \\ g_{n-1} &=& x_0 &+& x_1w^{n-1} &+&x_2w^{2(n-1)}&+&...&+&x_nw^{n(n-1)} \end{cases} ⎩⎪⎪⎪⎨⎪⎪⎪⎧g0g1⋯gn−1===x0x0x0+++x1x1wx1wn−1+++x2x2w2x2w2(n−1)+++.........+++xnxnwnxnwn(n−1)
列出其增广矩阵:
det ( ( 1 1 . . . 1 w w 2 . . . w n ⋮ ⋮ ⋱ ⋮ w n − 1 w 2 ( n − 1 ) ⋯ w n ( n − 1 ) ) ) = ∏ i < j ( w i − w j ) \det(\begin{pmatrix} 1 & 1 & ... & 1\\w & w^2 & ... & w^n \\ \vdots & \vdots &\ddots &\vdots \\ w^{n-1} & w^{2(n-1)} & \cdots & w^{n(n-1)} \end{pmatrix}) = \prod_{i<j}(w^i-w^j) det(⎝⎜⎜⎜⎛1w⋮wn−11w2⋮w2(n−1)......⋱⋯1wn⋮wn(n−1)⎠⎟⎟⎟⎞)=i<j∏(wi−wj)
Vandermonde矩阵行列式不为0,则存在唯一解 x i = ∑ a x i g j x_i = \sum a_{x_i}g_j xi=∑axigj,即存在唯一表示 f = ∑ m 0 , m 1 , . . . , m n − 1 a m 0 , m 1 , . . . , m n − 1 g 0 m 0 . . . g n − 1 m n − 1 f=\sum_{m_0,m_1,...,m_{n-1}}a_{m_0,m_1,...,m_{n-1}}g_0^{m_0}...g_{n-1}^{m_{n-1}} f=∑m0,m1,...,mn−1am0,m1,...,mn−1g0m0...gn−1mn−1
又:
f ( x 1 , x 2 , . . . , x n ) = h ( g 0 , g 1 , . . . , g n − 1 ) = h ( ∑ i x i , ∑ i x i w i , . . . , ∑ i x i w i ( n − 1 ) ) f(x_1,x_2,...,x_n) = h(g_0,g_1,...,g_{n-1}) = h(\sum_{i}x_i,\sum_{i}x_iw^i,...,\sum_{i}x_iw^{i(n-1)}) f(x1,x2,...,xn)=h(g0,g1,...,gn−1)=h(∑ixi,∑ixiwi,...,∑ixiwi(n−1))
f ( x n , x 1 , . . . , x n − 1 ) = h ( g 0 , w g 1 , . . . , w n − 1 g n − 1 ) f(x_n,x_1,...,x_{n-1}) = h(g_0,wg_1,...,w^{n-1}g_{n-1}) f(xn,x1,...,xn−1)=h(g0,wg1,...,wn−1gn−1)
f = ∑ m 0 , m 1 , . . . , m n − 1 a m 0 , m 1 , . . . , m n − 1 g 0 m 0 . . . g n − 1 m n − 1 = ∑ m 0 , m 1 , . . . , m n − 1 a m 0 , m 1 , . . . , m n − 1 ( w g 0 ) m 0 . . . ( w g n − 1 ) m n − 1 = ∑ m 0 , m 1 , . . . , m n − 1 w m 1 + 2 m 2 + . . . + ( n − 1 ) m n − 1 a m 0 , m 1 , . . . , m n − 1 ( w g 0 ) m 0 . . . ( w g n − 1 ) m n − 1 \begin{aligned}f&=\sum_{m_0,m_1,...,m_{n-1}}a_{m_0,m_1,...,m_{n-1}}g_0^{m_0}...g_{n-1}^{m_{n-1}} \\&= \sum_{m_0,m_1,...,m_{n-1}}a_{m_0,m_1,...,m_{n-1}}(wg_0)^{m_0}...(wg_{n-1})^{m_{n-1}}\\&=\sum_{m_0,m_1,...,m_{n-1}}w^{m_1+2m_2+...+(n-1)m_{n-1}}a_{m_0,m_1,...,m_{n-1}}(wg_0)^{m_0}...(wg_{n-1})^{m_{n-1}}\end{aligned} f=m0,m1,...,mn−1∑am0,m1,...,mn−1g0m0...gn−1mn−1=m0,m1,...,mn−1∑am0,m1,...,mn−1(wg0)m0...(wgn−1)mn−1=m0,m1,...,mn−1∑wm1+2m2+...+(n−1)mn−1am0,m1,...,mn−1(wg0)m0...(wgn−1)mn−1
对比系数可知 n ∣ m 1 + 2 m 2 + . . . + ( n − 1 ) m n − 1 n|m_1+2m_2+...+(n-1)m_{n-1} n∣m1+2m2+...+(n−1)mn−1
求下列行列式:
(1)
∣ 1 2 3 4 2 3 4 1 3 4 1 2 4 1 2 3 ∣ \left |\begin{matrix}1 & 2 & 3 & 4 \\ 2 & 3 & 4 & 1 \\ 3 &4 & 1 & 2 \\4 & 1 & 2 & 3\end{matrix}\right | ∣∣∣∣∣∣∣∣1234234134124123∣∣∣∣∣∣∣∣
可直接进行行列变换。 也有循环矩阵的一般求解形式:https://wenku.baidu.com/view/bf28cb59f01dc281e53af0ff.html
(4)
∣ a b c d − b a d − c − c − d a b − d c − b a ∣ \left |\begin{matrix}a & b & c & d \\ -b & a & d & -c \\ -c & -d & a & b \\-d & c & -b & a\end{matrix}\right | ∣∣∣∣∣∣∣∣a−b−c−dba−dccda−bd−cba∣∣∣∣∣∣∣∣
注意两行点乘值为0,然后用 ∣ A A T ∣ = ∣ A ∣ 2 |AA^T| = |A|^2 ∣AAT∣=∣A∣2计算。
记:
D = ∣ a 1 x 1 b 1 x 1 a 1 x 2 b 1 x 2 a 1 x 3 b 1 x 3 a 2 x 1 b 2 x 1 a 2 x 2 b 2 x 2 a 3 x 3 b 3 x 3 a 1 y 1 b 1 y 1 a 1 y 2 b 1 y 2 a 1 y 3 b 1 y 3 a 2 y 1 b 2 y 1 a 2 y 2 b 2 y 2 a 2 y 3 b 2 y 3 a 1 z 1 b 1 z 1 a 1 z 2 b 1 z 2 a 1 z 3 b 1 z 3 a 2 z 1 b 2 z 1 a 2 z 2 b 2 z 2 a 2 z 3 b 2 z 3 ∣ D = \left |\begin{matrix}a_1x_1 & b_1x_1 & a_1x_2 & b_1x_2 & a_1x_3 & b_1x_3 \\ a_2x_1 & b_2x_1 & a_2x_2 & b_2x_2 & a_3x_3 & b_3x_3 \\ a_1y_1 & b_1y_1 & a_1y_2 & b_1y_2 & a_1y_3 & b_1y_3 \\ a_2y_1 & b_2y_1 & a_2y_2 & b_2y_2 & a_2y_3 & b_2y_3\\ a_1z_1 & b_1z_1 & a_1z_2 & b_1z_2 & a_1z_3 & b_1z_3 \\ a_2z_1 & b_2z_1 & a_2z_2 & b_2z_2 & a_2z_3 & b_2z_3\\ \end{matrix}\right | D=∣∣∣∣∣∣∣∣∣∣∣∣a1x1a2x1a1y1a2y1a1z1a2z1b1x1b2x1b1y1b2y1b1z1b2z1a1x2a2x2a1y2a2y2a1z2a2z2b1x2b2x2b1y2b2y2b1z2b2z2a1x3a3x3a1y3a2y3a1z3a2z3b1x3b3x3b1y3b2y3b1z3b2z3∣∣∣∣∣∣∣∣∣∣∣∣
δ = ∣ a 1 b 1 a 2 b 2 ∣ \delta = \left| \begin{matrix}a_1 & b_1 \\ a_2 & b_2\end{matrix}\right| δ=∣∣∣∣a1a2b1b2∣∣∣∣
Δ = ∣ x 1 x 2 x 3 y 1 y 2 y 3 z 1 z 2 z 3 ∣ \Delta = \left| \begin{matrix}x_1 & x_2 & x_3\\ y_1 & y_2 & y_3 \\ z_1 & z_2 & z_3\end{matrix}\right| Δ=∣∣∣∣∣∣x1y1z1x2y2z2x3y3z3∣∣∣∣∣∣
证明: D = δ 3 Δ 2 D= \delta^3\Delta^2 D=δ3Δ2
构造两个矩阵,乘积为所求矩阵。 且行列式分别为 δ 3 \delta^3 δ3, Δ 2 \Delta^2 Δ2。
设 b i , j = ( a i , 1 + a i , 2 + ⋯ + a i , n ) − a i , j , 1 ≤ i , j ≤ n b_{i,j} = (a_{i,1}+a_{i,2}+\cdots+a_{i,n}) - a_{i,j}, 1\le i,j \le n bi,j=(ai,1+ai,2+⋯+ai,n)−ai,j,1≤i,j≤n。证明: ∣ b i , j ∣ n = ( − 1 ) n − 1 ( n − 1 ) ∣ a i , j ∣ n |b_{i,j}|_{n} = (-1)^{n-1}(n-1)|a_{i,j}|_n ∣bi,j∣n=(−1)n−1(n−1)∣ai,j∣n
这种每行有相同的元素的题可以考虑加边。
求 n n n阶行列式:
Δ n = ∣ 1 1 ⋯ 1 x 1 x 2 ⋯ x n x 1 2 x 2 2 ⋯ x n 2 . . . x 1 k − 1 x 2 k − 1 ⋯ x n k − 1 x 1 k + 1 x 2 k + 1 ⋯ x n k + 1 . . . ∣ \Delta_n = \left| \begin{matrix}1 & 1 & \cdots & 1\\ x_1 & x_2 & \cdots& x_n \\ x_1^2 & x_2^2 & \cdots&x_n^2 \\ &... \\ x_1^{k-1} & x_2^{k-1} & \cdots&x_n^{k-1}\\x_1^{k+1} & x_2^{k+1} & \cdots&x_n^{k+1} \\ & ... \\\end{matrix}\right| Δn=∣∣∣∣∣∣∣∣∣∣∣∣∣∣1x1x12x1k−1x1k+11x2x22...x2k−1x2k+1...⋯⋯⋯⋯⋯1xnxn2xnk−1xnk+1∣∣∣∣∣∣∣∣∣∣∣∣∣∣
补齐 x i k x_i^k xik行,最后一列新增未定元 x x x,然后答案为Vandermonde行列式中 x k x^k xk的系数。
(5)
求:
Δ = ∣ x a a ⋯ a a − a x a ⋯ a a ⋯ ⋯ ⋯ ⋯ − a − a − a ⋯ x a − a − a − a ⋯ − a x ∣ \Delta = \left| \begin{matrix}x & a & a & \cdots & a & a\\ -a & x & a & \cdots & a & a \\ &&\cdots\cdots\cdots\cdots \\-a & -a &-a & \cdots & x & a \\ -a & -a &-a & \cdots & -a & x\end{matrix}\right| Δ=∣∣∣∣∣∣∣∣∣∣x−a−a−aax−a−aaa⋯⋯⋯⋯−a−a⋯⋯⋯⋯aax−aaaax∣∣∣∣∣∣∣∣∣∣
类似反对称行列式,把最后一列全提个 a a a出来得到一个递推式,第一列全提个 − a -a −a出来得到一个递推式,然后解方程即可。
(10)
求 ∣ I m + A m , 2 ∗ B 2 , m ∣ |I_m + A_{m,2} * B_{2,m}| ∣Im+Am,2∗B2,m∣,其中 A m , 2 = ∣ a 1 1 a 2 1 ⋯ a m 1 ∣ , B 2 , m = ∣ b 1 b 2 ⋯ b m 1 1 ⋯ 1 ∣ A_{m,2} = \left|\begin{matrix}a_1 & 1 \\a_2 & 1 \\ &\cdots \\a_m &1\end{matrix}\right|, B_{2,m} =\left| \begin{matrix}b_1 & b_2 & \cdots & b_m \\ 1 & 1 & \cdots & 1\end{matrix}\right| Am,2=∣∣∣∣∣∣∣∣a1a2am11⋯1∣∣∣∣∣∣∣∣,B2,m=∣∣∣∣b11b21⋯⋯bm1∣∣∣∣。
用打洞原理, ∣ I m + A m , n ∗ B n , m ∣ = ∣ I n + A m , n T B n , m T ∣ |I_m + A_{m,n}*B_{n,m}| = |I_n + A_{m,n}^T B_{n,m}^T| ∣Im+Am,n∗Bn,m∣=∣In+Am,nTBn,mT∣,然后就只有四个数了。
(12)
∣ ( m k ) ( m k + 1 ) ⋯ ( m k + n − 1 ) ( m + 1 k ) ( m + 1 k + 1 ) ⋯ ( m + 1 k + n − 1 ) ⋯ ⋯ ⋯ ⋯ ( m + n − 1 k ) ( m + n − 1 k + 1 ) ⋯ ( m + n − 1 k + n − 1 ) ∣ \left| \begin{matrix} \binom{m}{k} & \binom{m}{k+1} & \cdots & \binom{m}{k+n-1} \\ \binom{m+1}{k} & \binom{m+1}{k+1} & \cdots & \binom{m+1}{k+n-1} \\ &&\cdots\cdots\cdots\cdots \\\binom{m+n-1}{k} & \binom{m+n-1}{k+1} & \cdots & \binom{m+n-1}{k+n-1}\end{matrix}\right| ∣∣∣∣∣∣∣∣(km)(km+1)(km+n−1)(k+1m)(k+1m+1)(k+1m+n−1)⋯⋯⋯⋯⋯⋯⋯(k+n−1m)(k+n−1m+1)(k+n−1m+n−1)∣∣∣∣∣∣∣∣
每行提一个 1 k ! \frac1{k!} k!1,每列提一个 m m m,然后变成一个子问题,最后要求这个矩阵( m i m_i mi = m 1 + i − 1 m_1 + i - 1 m1+i−1):
∣ 1 ( m 1 1 ) ( m 1 2 ) ⋯ ( m 1 n − 1 ) 1 ( m 2 1 ) ( m 2 2 ) ⋯ ( m 2 n − 1 ) ⋯ ⋯ ⋯ ⋯ 1 ( m n 1 ) ( m n 2 ) ⋯ ( m n n − 1 ) ∣ \left| \begin{matrix} 1 & \binom{m_1}{1} & \binom{m_1}{2} & \cdots & \binom{m_1}{n-1} \\ 1 & \binom{m_2}{1} & \binom{m_2}{2} & \cdots & \binom{m_2}{n-1} \\ &&\cdots\cdots\cdots\cdots \\1 & \binom{m_n}{1} & \binom{m_n}{2} & \cdots & \binom{m_n}{n-1}\end{matrix}\right| ∣∣∣∣∣∣∣∣111(1m1)(1m2)(1mn)(2m1)(2m2)⋯⋯⋯⋯(2mn)⋯⋯⋯(n−1m1)(n−1m2)(n−1mn)∣∣∣∣∣∣∣∣
上面这个矩阵每列提一个 1 k ! \frac1{k!} k!1变成下降幂,然后下降幂通过列变换变成Vandermonde矩阵。
(14)
∣ 1 0 0 ⋯ 0 1 1 ( 1 1 ) 0 ⋯ 0 x 1 ( 2 1 ) ( 2 2 ) ⋯ 0 x 2 ⋯ ⋯ ⋯ ⋯ 1 ( n − 2 1 ) ( n − 2 2 ) ⋯ ( n − 2 n − 2 ) x n − 2 1 ( n − 1 1 ) ( n − 1 2 ) ⋯ ( n − 1 n − 2 ) x n − 1 ∣ \left| \begin{matrix} 1 & 0 & 0 & \cdots & 0 & 1 \\ 1 & \binom{1}{1} & 0 & \cdots & 0 & x \\ 1 & \binom{2}{1} & \binom{2}{2} & \cdots & 0 & x^2 \\ &&\cdots\cdots\cdots\cdots \\ 1 & \binom{n-2}{1} & \binom{n-2}{2} & \cdots & \binom{n-2}{n-2} & x^{n-2} \\ 1 & \binom{n-1}{1} & \binom{n-1}{2} & \cdots & \binom{n-1}{n-2} & x^{n-1} \\\end{matrix}\right| ∣∣∣∣∣∣∣∣∣∣∣∣111110(11)(12)(1n−2)(1n−1)00(22)⋯⋯⋯⋯(2n−2)(2n−1)⋯⋯⋯⋯⋯000(n−2n−2)(n−2n−1)1xx2xn−2xn−1∣∣∣∣∣∣∣∣∣∣∣∣
f ( x + 1 ) = x n − 1 ⇒ f ( x ) = ( x − 1 ) n − 1 f(x+1) = x^{n-1} \Rightarrow f(x)=(x-1)^{n-1} f(x+1)=xn−1⇒f(x)=(x−1)n−1
(16)
∣ 1 cos θ 1 cos 2 θ 1 ⋯ cos ( n − 1 ) θ 1 1 cos θ 2 cos 2 θ 2 ⋯ cos ( n − 1 ) θ 2 ⋯ ⋯ ⋯ ⋯ 1 cos θ n cos 2 θ n ⋯ cos ( n − 1 ) θ n ∣ \left| \begin{matrix} 1 & \cos \theta_1 & \cos2\theta_1 & \cdots & \cos(n-1)\theta_1 \\ 1 & \cos \theta_2 & \cos2\theta_2 & \cdots & \cos(n-1)\theta_2 \\ &&\cdots\cdots\cdots\cdots \\1 & \cos \theta_n & \cos2\theta_n & \cdots & \cos(n-1)\theta_n \end{matrix}\right| ∣∣∣∣∣∣∣∣111cosθ1cosθ2cosθncos2θ1cos2θ2⋯⋯⋯⋯cos2θn⋯⋯⋯cos(n−1)θ1cos(n−1)θ2cos(n−1)θn∣∣∣∣∣∣∣∣
方法1: cos n θ \cos n\theta cosnθ是个关于 cos θ \cos\theta cosθ的多项式,然后用上题方法。
方法2:用复数表示 cos θ \cos \theta cosθ,然后随便搞搞。。
方法3:和差化积。
(17)
∣ x 1 − n x − 2 2 − ( n − 1 ) x − 4 ⋱ ⋱ ⋱ − 1 x − 2 n ∣ \left| \begin{matrix} x & 1 & & & \\ -n & x-2 & 2 & & \\ &-(n-1) & x-4 & \ddots\\ &&\ddots&\ddots \\ & & & &-1 & x-2n\end{matrix}\right| ∣∣∣∣∣∣∣∣∣∣x−n1x−2−(n−1)2x−4⋱⋱⋱−1x−2n∣∣∣∣∣∣∣∣∣∣
注意到每列和一样,且很稀疏,对每列求个前缀和然后对行差分,按最后一行展开归纳。
证明: ∏ 1 ≤ i < j ≤ n ( a i − a j ) \prod_{1 \le i \lt j \le n}(a_i-a_j) ∏1≤i<j≤n(ai−aj)能被 1 n − 1 2 n − 2 . . . ( n − 2 ) 2 ( n − 1 ) 1^{n-1}2^{n-2}...(n-2)^2(n-1) 1n−12n−2...(n−2)2(n−1)整除。
写成Vandermonde行列式,然后加成排列组合的形式,在每行除个阶乘得到上面某道题的形式。
证明偶阶斜对称方阵的行列式是个完全平方。
用1,2行消去下面行的第1,2列,然后得到的矩阵还是偶阶斜对称矩阵。 然后归纳。
设 ∀ i , a i , i > 0 , ∀ i ≠ k , a i , k < 0 , ∑ j a i , j > 0 \forall i , a_{i,i} > 0, \forall i \not = k, a_{i,k} < 0, \sum_{j}a_{i,j}>0 ∀i,ai,i>0,∀i=k,ai,k<0,∑jai,j>0,证明 ∣ a i , j ∣ n × n > 0 |a_{i,j}|_{n×n}>0 ∣ai,j∣n×n>0.
打洞后归纳。
证明:主角占优矩阵的行列式不为0.
如果等于0,则以 a i , j a_{i,j} ai,j为系数的齐次线性方程组有非0解。可推出矛盾。
把 n n n阶行列式 ∣ λ I − A ∣ |\lambda I - A| ∣λI−A∣展成 λ \lambda λ的多项式,并用 det A \det A detA的子式表达它的关于 λ \lambda λ的各次幂的系数,其中 A = ( a i , j ) n ∗ n A=(a_{i,j})_{n*n} A=(ai,j)n∗n
f ( λ ) f(\lambda) f(λ)求 i i i次导后带入0可得第 i i i项的答案,然后对矩阵求导即可。
设 A = ( a i , j ) A=(a_{i,j}) A=(ai,j)为 n n n阶方阵,其中 a i , j = ( i , j ) a_{i,j}=(i,j) ai,j=(i,j),求 ∣ A ∣ |A| ∣A∣。
利用 n = ∑ d ∣ n φ ( d ) n=\sum_{d|n}\varphi(d) n=∑d∣nφ(d),构造 B = ( b i , j ) , b i , j = [ i ∣ j ] B=(b_{i,j}),b_{i,j}=[i|j] B=(bi,j),bi,j=[i∣j], C = ( c i , j ) , c i , j = [ j ∣ i ] ∗ φ ( j ) C=(c_{i,j}),c_{i,j}=[j|i]*\varphi(j) C=(ci,j),ci,j=[j∣i]∗φ(j),则 ∣ B ∣ = 1 , ∣ C ∣ = ∏ i = 1 n φ ( i ) |B|=1,|C|=\prod_{i=1}^n\varphi(i) ∣B∣=1,∣C∣=∏i=1nφ(i),由 A = B C A=BC A=BC知 ∣ A ∣ = ∣ C ∣ |A|=|C| ∣A∣=∣C∣。
证明 ∀ A , B ∈ M n ∗ n ( F ) , A B − B A ≠ I \forall A,B\in M_{n*n}(F),AB-BA \not= I ∀A,B∈Mn∗n(F),AB−BA=I。
证:用 t r tr tr函数的可交换性, t r ( A B ) − t r ( B A ) = 0 ≠ t r ( I ) tr(AB)-tr(BA)=0 \not= tr(I) tr(AB)−tr(BA)=0=tr(I)。
(3)带入循环行列式公式求值即可。
(4)计算b-循环行列式的值。 详见https://baike.baidu.com/item/b%E5%BE%AA%E7%8E%AF%E8%A1%8C%E5%88%97%E5%BC%8F/22777133?fr=aladdin
考虑多项式的每项系数即可。
考虑Binet-Cauchy公式:
∣ A ∣ 2 = L a p l a c e 展 开 = [ ∑ B ( 1 , 2 , . . . , k i 1 , i 2 , . . . , i k ) C ( 1 , 2 , . . . , n − k i k + 1 , i k + 2 , . . . , i n ) ] 2 ≤ [ ∑ B ( 1 , 2 , . . . , k i 1 , i 2 , . . . , i k ) 2 ] [ ∑ C ( 1 , 2 , . . . , n − k i k + 1 , i k + 2 , . . . , i n ) 2 ] = B i n e t − C a u c h y 定 理 ∣ B ∣ ∣ C ∣ |A|^2 \xlongequal{Laplace展开} = [\sum B\binom{1,2,...,k}{i_1,i_2,...,i_k}C\binom{1,2,...,n-k}{i_{k+1},i_{k+2},...,i_{n}}]^2 \le [\sum B\binom{1,2,...,k}{i_1,i_2,...,i_k}^2][\sum C\binom{1,2,...,n-k}{i_{k+1},i_{k+2},...,i_{n}}^2]\xlongequal{Binet-Cauchy定理}|B||C| ∣A∣2Laplace展开 =[∑B(i1,i2,...,ik1,2,...,k)C(ik+1,ik+2,...,in1,2,...,n−k)]2≤[∑B(i1,i2,...,ik1,2,...,k)2][∑C(ik+1,ik+2,...,in1,2,...,n−k)2]Binet−Cauchy定理 ∣B∣∣C∣
##习题1
(3) w w w是 n n n 次单位根,求 A − 1 A^{-1} A−1,其中 a i , j = w i ( j − 1 ) a_{i,j}=w^{i(j-1)} ai,j=wi(j−1)。
逆矩阵为 B , b i , j = w − i ( j − 1 ) B,b_{i,j}=w^{-i(j-1)} B,bi,j=w−i(j−1)。FFT的逆变换。
(4)这是一个比较少元素的矩阵,可列方程组暴力求解。
设 A ∈ R 2 n × 2 n A\in R^{2n \times 2n} A∈R2n×2n,设KaTeX parse error: Undefined control sequence: \pmatrix at position 3: M=\̲p̲m̲a̲t̲r̲i̲x̲{0 & I_n\\-I_n&…,若 A M A T = M AMA^T=M AMAT=M,求证 ∣ A ∣ = 1 |A|=1 ∣A∣=1。
证:
∣ A ∣ 2 ∣ M ∣ = ∣ M ∣ ⇒ ∣ A ∣ 2 = 1 |A|^2|M|=|M| \Rightarrow |A|^2 = 1 ∣A∣2∣M∣=∣M∣⇒∣A∣2=1,往证 ∣ A ∣ = 1 |A|=1 ∣A∣=1。
方法1:
( A M + M A ) A T = M ( I + A A T ) (AM+MA)A^T = M(I+AA^T) (AM+MA)AT=M(I+AAT)
注意到KaTeX parse error: Undefined control sequence: \pmatrix at position 9: AM+MA = \̲p̲m̲a̲t̲r̲i̲x̲{B & C \\ -C & …,在复数域上作变换有 ∣ B C − C B ∣ = ∣ B + i C C − C + i B B ∣ = ∣ B + i C C 0 B − i C ∣ = ∣ B + i C ∣ ∣ B − i C ∣ \left|\begin{matrix}B & C\\-C & B\end{matrix}\right| =\left|\begin{matrix}B+iC & C \\ -C + iB & B\end{matrix}\right| =\left|\begin{matrix}B+iC & C \\ 0 & B-iC\end{matrix}\right| = |B+iC||B-iC| ∣∣∣∣B−CCB∣∣∣∣=∣∣∣∣B+iC−C+iBCB∣∣∣∣=∣∣∣∣B+iC0CB−iC∣∣∣∣=∣B+iC∣∣B−iC∣
在实数意义下 B + i C B+iC B+iC与 B − i C B-iC B−iC共轭,故行列式共轭,知 ∣ B + i C ∣ ∣ B − i C ∣ = ∣ B + i C ∣ 2 > 0 |B+iC||B-iC|=|B+iC|^2 > 0 ∣B+iC∣∣B−iC∣=∣B+iC∣2>0,又 I + A A T I+AA^T I+AAT正定, ∣ M ∣ = 1 |M|=1 ∣M∣=1,知 ∣ A T ∣ > 0 |A^T|>0 ∣AT∣>0
方法2(微小摄动法):
设 A = ( B C D E ) A=\binom{B \ C}{D\ E} A=(D EB C),则 A M A T = ( B C T − C B T B E T − C D T D C T − E B T D E T − E D T ) AMA^T = \binom{BC^T-CB^T \ BE^T-CD^T}{DC^T-EB^T DE^T-ED^T} AMAT=(DCT−EBTDET−EDTBCT−CBT BET−CDT) ⇒ B C T − C B T = 0 , D E T − E D T = 0 , B E T − C D T = I , D C T − E B T = I \Rightarrow BC^T-CB^T = 0, DE^T-ED^T = 0, BE^T - CD^T = I, DC^T-EB^T=I ⇒BCT−CBT=0,DET−EDT=0,BET−CDT=I,DCT−EBT=I。
若 B B B可逆,则 det ( B C D E ) = ∣ B C 0 E − D B − 1 C ∣ = det ( B E T − B C T ( B − 1 ) T D T ) = det ( B E T − C D T ) = 1 \det\binom{B \ C}{D \ E} = \left|\begin{matrix}B&C \\ 0 & E-DB^{-1}C\end{matrix}\right| = \det(BE^T-BC^T(B^{-1})^TD^T) = \det(BE^T-CD^T)=1 det(D EB C)=∣∣∣∣B0CE−DB−1C∣∣∣∣=det(BET−BCT(B−1)TDT)=det(BET−CDT)=1
否则,希望找到 X ≠ 0 X \not = 0 X=0,满足 X C T = C X T XC^T = CX^T XCT=CXT,从而 ( B + t X ) C T − C ( B + t X ) T = 0 (B+tX)C^T -C(B+tX)^T=0 (B+tX)CT−C(B+tX)T=0。
那么 X Q T I t P T = P I t Q X T ⇒ P − 1 X Q T I t = I t Q X T ( P − 1 ) T XQ^TI_tP^T=PI_tQX^T \Rightarrow P^{-1}XQ^T I_t =I_tQX^T(P^{-1})^T XQTItPT=PItQXT⇒P−1XQTIt=ItQXT(P−1)T,不难发现只要 P − 1 X Q T P^{-1}XQ^T P−1XQT满足 ( X 1 X 2 0 X 3 ) \binom{X_1 X_2}{0 \ X_3} (0 X3X1X2)即可,其中 X 1 T = X 1 X_1^T=X_1 X1T=X1,又因为必然存在任意小的 ϵ \epsilon ϵ,满足 B ′ = B + ϵ X B'=B+\epsilon X B′=B+ϵX可逆,则:
∣ B ′ C D E ∣ = det ( B ′ E T − C D T ) = det ( I + ϵ X E T ) \left|\begin{matrix}B' & C \\ D & E\end{matrix}\right|=\det(B'E^T - CD^T) = \det(I+\epsilon XE^T) ∣∣∣∣B′DCE∣∣∣∣=det(B′ET−CDT)=det(I+ϵXET),在上式中令 ϵ \epsilon ϵ趋于0,即得 det ( A ) > 0 \det(A)>0 det(A)>0。
(3) 计算Cauchy行列式的逆矩阵。
用行列变换的方法过于繁琐,因此介绍求Cauchy行列式的方法。
https://www.cnblogs.com/xixifeng/p/3932238.html
运用辗转相除法代替Gauss消元即可。
证明 n n n阶幂等方阵 A A A(即 A 2 = A A^2=A A2=A)的秩等于它的迹。
证:
A 2 = A ⇒ I r Q P I r = I r ⇒ Q P = ( I r B C D ) A^2=A \Rightarrow I_rQPI_r = I_r \Rightarrow QP=\binom{I_r \ B}{C \ D} A2=A⇒IrQPIr=Ir⇒QP=(C DIr B),故 t r ( P I r Q ) = t r ( Q P I r ) = r = r ( A ) tr(PI_rQ) = tr(QPI_r) = r=r(A) tr(PIrQ)=tr(QPIr)=r=r(A)。
设 A ∈ F m × n , B ∈ F n × p , C ∈ F p × q A\in F^{m\times n}, B \in F^{n \times p}, C \in F^{p \times q} A∈Fm×n,B∈Fn×p,C∈Fp×q,证明: r ( A B C ) + r ( B ) ≥ r ( A B ) + r ( B C ) r(ABC)+r(B) \ge r(AB)+r(BC) r(ABC)+r(B)≥r(AB)+r(BC)
证:
还是用打洞的思想。
( A B C 0 0 B ) → ( A B C 0 − B C B ) → ( 0 A B − B C B ) \begin{pmatrix}ABC &0 \\ 0 & B\end{pmatrix} \rightarrow \begin{pmatrix}ABC & 0 \\ -BC & B\end{pmatrix} \rightarrow\begin{pmatrix}0 &AB \\ -BC & B\end{pmatrix} (ABC00B)→(ABC−BC0B)→(0−BCABB)
设 A ∈ F m × n , B ∈ F p × q , C ∈ F m × q , X ∈ F n × q , Y ∈ F m × p A \in F^{m \times n},B \in F^{p\times q}, C \in F^{m \times q}, X \in F^{n \times q}, Y \in F^{m \times p} A∈Fm×n,B∈Fp×q,C∈Fm×q,X∈Fn×q,Y∈Fm×p,证明:
A X − Y B = C 有 解 ⇔ r ( A C 0 B ) = r ( A 0 0 B ) AX-YB=C 有解 \Leftrightarrow r(\begin{matrix}A & C \\ 0 & B\end{matrix})=r(\begin{matrix}A & 0 \\ 0 & B\end{matrix}) AX−YB=C有解⇔r(A0CB)=r(A00B)
思路:
P P P( A C 0 B \begin{matrix}A & C \\ 0 & B\end{matrix} A0CB)Q通过简单的行列变换可变为 P P P( A 0 0 B \begin{matrix}A & 0 \\ 0 & B\end{matrix} A00B)Q,然后构造出一组解。
证明:设 A A A是 n n n阶方阵,如果存在正整数 k k k,使得 r ( A k ) = r ( A k + 1 ) r(A^k) = r(A^{k+1}) r(Ak)=r(Ak+1),则 r ( A k ) = r ( A k + t ) , t ∈ N r(A^k)=r(A^{k+t}), t\in \N r(Ak)=r(Ak+t),t∈N
证:
r ( A A k A ) + r ( A k ) ≥ 2 r ( A k + 1 ) ⇒ A k + 2 = A k + 1 r(AA^{k}A) +r(A^k) \ge 2r(A^{k+1}) \Rightarrow A^{k+2}=A^{k+1} r(AAkA)+r(Ak)≥2r(Ak+1)⇒Ak+2=Ak+1
设 A , B A,B A,B为 n n n阶方阵, A B = B A = 0 AB=BA=0 AB=BA=0,且 r ( A 2 ) = r ( A ) r(A^2)=r(A) r(A2)=r(A)。证明 r ( A + B ) = r ( A ) + r ( B ) r(A+B)=r(A)+r(B) r(A+B)=r(A)+r(B)。
证:
打洞就完事了。 不过首先有一个引理,存在 C , s . t . A 2 C = A C,s.t.A^2C=A C,s.t.A2C=A,很显然,这里就不证了。
( A 0 0 B ) → ( A A + B 0 B ) → c 1 − c 2 ∗ A C ( 0 A + B 0 B ) → ( 0 A + B 0 − A ) → r 2 + r 1 ∗ A C ( 0 A + B 0 0 ) \begin{pmatrix}A &0 \\ 0 & B\end{pmatrix} \rightarrow \begin{pmatrix} A & A+B \\ 0 & B\end{pmatrix} \overset{c_1-c_2*AC}\rightarrow\begin{pmatrix}0 &A+B \\ 0 & B\end{pmatrix}\rightarrow\begin{pmatrix}0 &A+B \\ 0 & -A\end{pmatrix}\overset{r_2+r_1*AC}\rightarrow\begin{pmatrix}0 &A+B \\ 0 & 0\end{pmatrix} (A00B)→(A0A+BB)→c1−c2∗AC(00A+BB)→(00A+B−A)→r2+r1∗AC(00A+B0)